Academic Integrity Education

As educational institutions rush to deploy AI detection tools and process tracking systems to combat AI-generated content, we may be overlooking critical insights from decades of research on academic integrity - insights brilliantly synthesized in Tricia Bertram Gallant and David A. Rettinger's groundbreaking work "The Opposite of Cheating: Teaching for Integrity in the Age of AI." The current approach often prioritizes technological solutions: first, AI detection in text submissions; second, surveillance through process tracking. But this technological arms race may inadvertently widen what moral development psychologists call the "judgment-action gap" – the disconnect between knowing what's right and actually doing it. Research shows students typically fall into three moral categories regarding academic integrity: 1. Those who view cheating as a personal choice (against rules but acceptable) 2. Those who see it as against the rules but not inherently wrong 3. Those who view it as wrong regardless of rules or laws Unsurprisingly, students in the third category are least likely to cheat. But when students do violate rules they recognize, they engage in what researchers call "moral disengagement" through neutralization techniques: 1. Denial of responsibility ("I had no choice") 2. Denial of victim or harm ("No one gets hurt") 3. Condemnation of condemners ("The instructor doesn't even care") 4. Appeals to higher authority ("My future career is more important") Here's what's particularly concerning, and what Gallant and Rettinger help us understand with remarkable clarity: neutralization occurs most frequently when students perceive that instructors are implementing changes focused solely on catching cheaters rather than improving pedagogy. This creates a troubling paradox that aligns directly with principle #8 from their framework: our surveillance-focused approaches might yield short-term reductions in cheating behaviors while fostering long-term moral disengagement. Students become increasingly "neutralized" to the course content itself, viewing it merely as an obstacle to overcome rather than meaningful learning. As we navigate education in the AI era, perhaps our focus should shift from detection to designing authentic assessments that make cheating irrelevant – not because it's impossible, but because it's pointless compared to the value of genuine engagement. This perspective embodies the transformative approach that makes "The Opposite of Cheating" such an essential read for educators today. What has been your experience with anti-cheating measures? Have you observed this neutralization phenomenon in your educational context? Alfonso Mendoza Jr., M.Ed. France Q. Hoang Pat Yongpradit Scott Sommers, PhD Nigel P. Daly, PhD 戴 禮 Mike Kentz Lance Eaton, PhD Jason Gulya Phillip Alcock Thom Markham, Ph.D. Jessica L. Parker, Ed.D.

Academic Misconduct in Dental Schools: Is it just a warning sign—or a predictor of future professional misconduct? From simply passing a note during a didactic exam, to unauthorized use of generative AI, to clinical misconduct… Are we doing enough in dental schools to produce future generations of dentists with ethical values? In dental education, academic integrity is more than a rule. It’s a foundation for ethical patient care. And when that foundation cracks early—so does trust in the profession. ⸻ What does academic misconduct look like? ❌ Cheating – Using unauthorized materials during exams or assignments ❌ Plagiarism – Presenting someone else’s work as your own ❌ Fabrication – Falsifying data or sources ❌ Falsification – Providing false information for academic advantage ⸻ And now, a new layer: AI misuse ⚠️ AI-generated content – Submitting work created by AI tools without disclosure ⚠️ Automated shortcuts – Using AI to bypass learning, simulate answers, or complete clinical reflections ⚠️ Unclear policies – When AI use is not defined, misuse fills the gap AI can enhance learning—but without transparency and integrity, it becomes a tool for deception. ⸻ What are the consequences? ⚠️ Disciplinary action – From warnings to dismissal ⚠️ Transcript notations – That may follow you into job interviews ⚠️ Career risks – Integrity violations can derail licensure and trust ⸻ Why does this matter? ✔️ Trust – Degrees must be earned, not taken ✔️ Patient safety – Poor integrity leads to poor care ✔️ Equity – A fair system only works when everyone plays fair ✔️ AI literacy – Ethical use of technology is now a professional competency ⸻ How do we prevent misconduct? • Educate early and often – Definitions, boundaries, and consequences must be clear • Promote ethical culture – Respect and integrity must be modeled and reinforced • Address AI directly – Define its place in education, and enforce it • Support struggling students – Misconduct often masks academic anxiety ⸻ Academic integrity isn’t just about grades. It’s about who we become before we enter the clinic. Let’s lead the next generation by holding the highest standards— Not just for knowledge, but for character. What strategies has your school used to guide ethical AI use? #DentalEducation #AcademicIntegrity #AIInEducation #ProfessionalEthics #StudentSuccess #FutureDentists #HigherEdLeadership #IntegrityMatters #DentalStudents #EthicalLeadership #ResponsibleAI

There's a recurring theme in discussions about #academicintegrity in the age of AI that is echoed in this opinion piece and it goes something like: our traditional definitions of academic integrity require us to work against GenAI and so we need to redefine what academic integrity means. However, this is a false dichotomy. It's not an either/or in the sense of "either we resist technology or we redefine academic integrity." According to the International Center for Academic Integrity, academic integrity means the courage to be honest, respectful, fair, trustworthy and responsible even when it is difficult to do so. That definition is timeless and independent of current technological trends and classroom contexts. I think this false dichotomy (either we resist tech or we change of definition of academic integrity) persists because most people conflate academic integrity with academic dishonesty or with policy. For example, in this piece, the authors imply that using AI is only cheating if its "use violates an explicit policy prohibiting it." And that academic integrity traditionally means "policing student behavior". The authors are correct that the issue is complicated, and it is made even more complicated if we hang on to this very limited conception of academic integrity. Attending to academic integrity means thinking deeply about how to facilitate and validate learning with or without GenAI. It means communicating clearly to students the learning expectations and why they are being asked to demonstrate their learning in certain ways. It means teaching students about honest and responsible use of technology and not offloading their humanity to it. It means acknowledging that sometimes we have to help students demonstrate their learning with integrity by securing some assessments. And it means attending to the ways in which we show up in the classroom and leveraging the inevitable mistakes students will make to further advance their learning and human development. Academic integrity does not need redefining or reconsideration in the age of AI. Our approach to teaching, learning and assessment, on the other hand, does.

🎓 Leading with Integrity in the Age of AI 🤖 Education leaders Randy Kolset and Mike Lawrence are charting a new path for how schools can balance innovation with integrity in the age of AI. In their EdTech Digest column, “Practice What You Teach: Academic Integrity and AI,” they spotlight a quiet contradiction: 👉 Students are asked to disclose AI use — but teachers often aren’t. Their solution? Build systems of trust, not suspicion. They highlight forward-thinking districts putting this into practice: ✅ Laguna Beach Unified School District’s “AI: Trust You” framework that makes AI use transparent for all ✅ Orange Unified School District’s guidelines empowering educators while maintaining accountability ✅ ABC Unified School District’s AI Trust & Transparency badges that visualize human + AI collaboration Their message is both practical and inspiring: “Start a conversation, not an accusation.” If your district is shaping its AI policy, this piece is a roadmap — turning compliance into culture and technology into trust. 🔗 Read the full article → https://lnkd.in/e-DnUM8F #EdTechLeadership #AIinEducation #AcademicIntegrity #K12Innovation #TrustInTech #DigitalEthics also hat tip to Dr. Sabba Quidwai and Richard Culatta